Segmentation and estimation of change-point models: false positive control and confidence regions

DOI10.1214/19-AOS1861zbMath1451.62035arXiv1608.03032MaRDI QIDQ2196238

Jian Li, Xiao Fang, David O. Siegmund

Publication date: 28 August 2020

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1608.03032

zbMATH Keywords

exponential familieslikelihood ratio statisticsconfidence regionschange-pointsarray CGH analysiscomparative genomic hybridization (CGH)

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Nonparametric tolerance and confidence regions (62G15) Protein sequences, DNA sequences (92D20)

Related Items

Detecting possibly frequent change-points: wild binary segmentation 2 and steepest-drop model selection -- rejoinder, Detecting Multiple Change Points: The PULSE Criterion, Multiscale change point detection via gradual bandwidth adjustment in moving sum processes, Bayesian Change Point Detection with Spike-and-Slab Priors, Bootstrap confidence intervals for multiple change points based on moving sum procedures, Detecting multiple generalized change-points by isolating single ones, Multiscale change-point segmentation: beyond step functions

Uses Software

• wbs

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